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In this paper we present our first participation at RepLab Campaign. Our work is focused in two contributions. The first one is the use of an IR method to address Polarity and Filtering tasks. These two tasks can be seen as the same problem: to find the most relevant class to annotate a given tweet. For that, we applied a classical IR approach, using the(More)
This paper summarizes the participation of UNED at the 2014 Retrieving Diverse Social Images Task [3]. We propose a novel approach based on Formal Concept Analysis (FCA) to detect the latent topics related to the images and a later Hierarchical Agglomerative Clustering (HAC) to put together the images according to these latent topics. The diversification(More)
The main goal of this paper it is to present our experiments in ImageCLEF 2011 Campaign (Medical Retrieval Task). This edition we use textual and visual information, based on the assumption that the textual module better captures the meaning of a topic. So that, the TBIR module works firstly and acts as a filter, and the CBIR system reorder the textual(More)
The UNED-UV group at the ImageCLEF2013 Campaign have participated in the Scalable Concept Image Annotation subtask. We present a mul-timedia IR-based system for the annotation task. In this collection, the images do not have any textual description associated, so we have downloaded and pre-processed the web pages which contain the images. Regarding the(More)
This paper presents our submitted experiments in the Concept annotation and Concept Retrieval tasks using Flickr photos at ImageCLEF 2012. This edition we applied new strategies for both the textual and the visual subsystems included in our multimodal retrieval system. The visual subsystem has focus on extending the low-level features vector with concept(More)
The main goal of this paper is to present our experiments in the classification modality and in the ad-hoc image retrieval tasks with the Medical collection at ImageCLEF 2012 Campaign. This edition we focus on applying new strategies for both the textual and the visual subsystems included in our multimodal retrieval system. The visual subsystem has focus on(More)
In a recommendation task it is crucial to have an accurate content-based description of the users and the items consumed by them. Linked Open Data (LOD) has been demonstrated as one of the best ways of obtaining this kind of content, given its huge amount of structured information. The main question is to know how useful the LOD information is in inferring(More)
This paper summarizes our participation in the CLEF-NEWSREEL 2014 Challenge. The challenge focused on the recommendation of news articles. UNED's participation is in the " Recommend news articles in real-time " task. To address the recommendation tasks, a Formal Concept Analysis framework is proposed to first create the recommendation models and second to(More)